• Title/Summary/Keyword: MusicSearch

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Differences in Perceptions of Usage and Intention to Continuous Use of AI Speakers: Focusing on Functions of Music, News, and Search (AI 스피커의 기능별 이용 인식과 지속 이용 의도의 차이: 음악, 뉴스, 검색을 중심으로)

  • Kim, Young Ju;Kim, Sung Tae;Kim, Hyoung-Jee
    • The Journal of the Korea Contents Association
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    • v.20 no.11
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    • pp.644-655
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    • 2020
  • The study examined differences between perceptions of AI speakers and intention to continuous use of AI speakers according to usage function. We divided usage patterns into single- and multi-function orientations based on the usage by different functions of audio content (music, news, and search), and analyzed the differences between perceptions of using AI speakers and the intention to continuous use. 335 men and women who had experience using AI speakers participated in an online survey. Results are as follows. First, men used AI speakers mainly for acquiring news, and the extent to which 20s and 40s acquire news was different. Second, perceptions of usefulness and ease of use were found to be higher in the multi-functional group(music-news-search). Last, regarding the intention to continuous use of AI speakers, the multi-functional group was highest, and users focusing on music listening were relatively higher than users for other functions. The findings of the study are expected to be used as foundational data for expanding the use of AI speakers and developing strategies for service provision in each AI speaker brand.

Case study of Music & Imagery for Woman with Depression (우울한 내담자를 위한 MI(Music & Imagery) 치료사례)

  • Song, In Ryeong
    • Journal of Music and Human Behavior
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    • v.5 no.1
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    • pp.67-90
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    • 2008
  • This case used MI techniques that give an imagery experience to depressed client's mental resource, and that makes in to verbalism. Also those images are supportive level therapy examples that apply to positive variation. MI is simple word of 'Music and Imagery' with one of psychology cure called GIM(Guided Imagery and Music). It makes client can through to the inner world and search, confront, discern and solve with suitable music. Supportive Level MI is only used from safety level music. Introduction of private session can associate specification feeling, subject, word or image. And those images are guide to positive experience. The First session step of MI program is a prelude that makes concrete goal like first interview. The Second step is a transition that can concretely express about client's story. The third step is induction and music listening. And it helps to associate imagery more easily by used tension relaxation. Also it can search and associate about various imagery from the music. The last step is process that process drawing imagery, talking about personal imagery experience in common with therapist that bring the power by expansion the positive experience. Client A case targets rapport forming(empathy, understanding and support), searching positive recourse(child hood, family), client's emotion and positive support. Music must be used simple tone, repetition melody, steady rhythm and organized by harmony music of what therapist and client's preference. The client used defense mechanism and couldn't control emotion by depression in 1 & 2 sessions. But the result was client A could experience about support and understanding after 3 sessions. After session 4 the client had stable, changed to positive emotion from the negative emotion and found her spontaneous. Therefore, at the session 6, the client recognized that she will have step of positive time at the future. About client B, she established rapport forming(empathy, understanding and support) and searching issues and positive recognition(child hood, family), expression and insight(present, future). The music was comfortable, organizational at the session 1 & 2, but after session 3, its development was getting bigger and the main melody changed variation with high and low of tune. Also it used the classic and romantic music. The client avoids bad personal relations to religious relationship. But at the session 1 & 2, client had supportive experience and empathy because of her favorite, supportive music. After session 3, client B recognized and face to face the present issue. But she had avoidance and face to face of ambivalence. The client B had a experience about emotion change according depression and face to face client's issues After session 4. At the session 5 & 6, client tried to have will power of healthy life and fairly attitude, train mental power and solution attitude in the future. On this wise, MI program had actuality and clients' issues solution more than GIM program. MI can solute the issue by client's based issue without approach to unconsciousness like GIM. Especially it can use variety music and listening time is shorter than GIM and structuralize. Also can express client's emotion very well. So it can use corrective and complement MI program to children, adolescent and adult.

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Development of Music Recommendation System based on Customer Sentiment Analysis (소비자 감성 분석 기반의 음악 추천 알고리즘 개발)

  • Lee, Seung Jun;Seo, Bong-Goon;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.197-217
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    • 2018
  • Music is one of the most creative act that can express human sentiment with sound. Also, since music invoke people's sentiment to get empathized with it easily, it can either encourage or discourage people's sentiment with music what they are listening. Thus, sentiment is the primary factor when it comes to searching or recommending music to people. Regard to the music recommendation system, there are still lack of recommendation systems that are based on customer sentiment. An algorithm's that were used in previous music recommendation systems are mostly user based, for example, user's play history and playlists etc. Based on play history or playlists between multiple users, distance between music were calculated refer to basic information such as genre, singer, beat etc. It can filter out similar music to the users as a recommendation system. However those methodology have limitations like filter bubble. For example, if user listen to rock music only, it would be hard to get hip-hop or R&B music which have similar sentiment as a recommendation. In this study, we have focused on sentiment of music itself, and finally developed methodology of defining new index for music recommendation system. Concretely, we are proposing "SWEMS" index and using this index, we also extracted "Sentiment Pattern" for each music which was used for this research. Using this "SWEMS" index and "Sentiment Pattern", we expect that it can be used for a variety of purposes not only the music recommendation system but also as an algorithm which used for buildup predicting model etc. In this study, we had to develop the music recommendation system based on emotional adjectives which people generally feel when they listening to music. For that reason, it was necessary to collect a large amount of emotional adjectives as we can. Emotional adjectives were collected via previous study which is related to them. Also more emotional adjectives has collected via social metrics and qualitative interview. Finally, we could collect 134 individual adjectives. Through several steps, the collected adjectives were selected as the final 60 adjectives. Based on the final adjectives, music survey has taken as each item to evaluated the sentiment of a song. Surveys were taken by expert panels who like to listen to music. During the survey, all survey questions were based on emotional adjectives, no other information were collected. The music which evaluated from the previous step is divided into popular and unpopular songs, and the most relevant variables were derived from the popularity of music. The derived variables were reclassified through factor analysis and assigned a weight to the adjectives which belongs to the factor. We define the extracted factors as "SWEMS" index, which describes sentiment score of music in numeric value. In this study, we attempted to apply Case Based Reasoning method to implement an algorithm. Compare to other methodology, we used Case Based Reasoning because it shows similar problem solving method as what human do. Using "SWEMS" index of each music, an algorithm will be implemented based on the Euclidean distance to recommend a song similar to the emotion value which given by the factor for each music. Also, using "SWEMS" index, we can also draw "Sentiment Pattern" for each song. In this study, we found that the song which gives a similar emotion shows similar "Sentiment Pattern" each other. Through "Sentiment Pattern", we could also suggest a new group of music, which is different from the previous format of genre. This research would help people to quantify qualitative data. Also the algorithms can be used to quantify the content itself, which would help users to search the similar content more quickly.

An Efficient Frequent Melody Indexing Method to Improve Performance of Query-By-Humming System (허밍 질의 처리 시스템의 성능 향상을 위한 효율적인 빈번 멜로디 인덱싱 방법)

  • You, Jin-Hee;Park, Sang-Hyun
    • Journal of KIISE:Databases
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    • v.34 no.4
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    • pp.283-303
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    • 2007
  • Recently, the study of efficient way to store and retrieve enormous music data is becoming the one of important issues in the multimedia database. Most general method of MIR (Music Information Retrieval) includes a text-based approach using text information to search a desired music. However, if users did not remember the keyword about the music, it can not give them correct answers. Moreover, since these types of systems are implemented only for exact matching between the query and music data, it can not mine any information on similar music data. Thus, these systems are inappropriate to achieve similarity matching of music data. In order to solve the problem, we propose an Efficient Query-By-Humming System (EQBHS) with a content-based indexing method that efficiently retrieve and store music when a user inquires with his incorrect humming. For the purpose of accelerating query processing in EQBHS, we design indices for significant melodies, which are 1) frequent melodies occurring many times in a single music, on the assumption that users are to hum what they can easily remember and 2) melodies partitioned by rests. In addition, we propose an error tolerated mapping method from a note to a character to make searching efficient, and the frequent melody extraction algorithm. We verified the assumption for frequent melodies by making up questions and compared the performance of the proposed EQBHS with N-gram by executing various experiments with a number of music data.

Music as a Therapeutic Intervention for Patients with Schizophrenia: Systematic Review (조현병 환자 대상 음악중재에 대한 체계적 고찰)

  • Kim, Young Shil
    • Journal of Music and Human Behavior
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    • v.12 no.2
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    • pp.37-60
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    • 2015
  • The purpose of this study was to systematically review music intervention studies for patients with schizophrenia. The researcher searched nine electronic databases for clinical trials published since 2000, using combinations of keyword related to schizophrenia and music interventions. The initial search identified 272 studies, and fifteen studies were selected by reviewing the titles, abstracts and full articles, In addition, three articles were added by examining other review articles. Thus, a total of 18 articles were analyzed in terms of their general and intervention characteristics, and the PEDro scale was used to evaluate the methodological quality of the included studies. The results demonstrated that, due to the lack of randomization and blinding, the methodological qualities of the studies with high quality music interventions were often rated low. Eight Music interventions conducted by qualified music therapists included active music-making, therapeutic relationship, and supervision systems for improving intervention quality. In conclusion, the randomization, blinding, and the therapeutic rationale of intervention are recommended in future clinical trials for patients with schizophrenia.

Musician Search in Time-Series Pattern Index Files using Features of Audio (오디오 특징계수를 이용한 시계열 패턴 인덱스 화일의 뮤지션 검색 기법)

  • Kim, Young-In
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.5 s.43
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    • pp.69-74
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    • 2006
  • The recent development of multimedia content-based retrieval technologies brings great attention of musician retrieval using features of a digital audio data among music information retrieval technologies. But the indexing techniques for music databases have not been studied completely. In this paper, we present a musician retrieval technique for audio features using the space split methods in the time-series pattern index file. We use features of audio to retrieve the musician and a time-series pattern index file to search the candidate musicians. Experimental results show that the time-series pattern index file using the rotational split method is efficient for musician retrievals in the time-series pattern files.

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An Embedding /Extracting Method of Audio Watermark Information for High Quality Stereo Music (고품질 스테레오 음악을 위한 오디오 워터마크 정보 삽입/추출 기술)

  • Bae, Kyungyul
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.21-35
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    • 2018
  • Since the introduction of MP3 players, CD recordings have gradually been vanishing, and the music consuming environment of music users is shifting to mobile devices. The introduction of smart devices has increased the utilization of music through music playback, mass storage, and search functions that are integrated into smartphones and tablets. At the time of initial MP3 player supply, the bitrate of the compressed music contents generally was 128 Kbps. However, as increasing of the demand for high quality music, sound quality of 384 Kbps appeared. Recently, music content of FLAC (Free License Audio Codec) format using lossless compression method is becoming popular. The download service of many music sites in Korea has classified by unlimited download with technical protection and limited download without technical protection. Digital Rights Management (DRM) technology is used as a technical protection measure for unlimited download, but it can only be used with authenticated devices that have DRM installed. Even if music purchased by the user, it cannot be used by other devices. On the contrary, in the case of music that is limited in quantity but not technically protected, there is no way to enforce anyone who distributes it, and in the case of high quality music such as FLAC, the loss is greater. In this paper, the author proposes an audio watermarking technology for copyright protection of high quality stereo music. Two kinds of information, "Copyright" and "Copy_free", are generated by using the turbo code. The two watermarks are composed of 9 bytes (72 bits). If turbo code is applied for error correction, the amount of information to be inserted as 222 bits increases. The 222-bit watermark was expanded to 1024 bits to be robust against additional errors and finally used as a watermark to insert into stereo music. Turbo code is a way to recover raw data if the damaged amount is less than 15% even if part of the code is damaged due to attack of watermarked content. It can be extended to 1024 bits or it can find 222 bits from some damaged contents by increasing the probability, the watermark itself has made it more resistant to attack. The proposed algorithm uses quantization in DCT so that watermark can be detected efficiently and SNR can be improved when stereo music is converted into mono. As a result, on average SNR exceeded 40dB, resulting in sound quality improvements of over 10dB over traditional quantization methods. This is a very significant result because it means relatively 10 times improvement in sound quality. In addition, the sample length required for extracting the watermark can be extracted sufficiently if the length is shorter than 1 second, and the watermark can be completely extracted from music samples of less than one second in all of the MP3 compression having a bit rate of 128 Kbps. The conventional quantization method can extract the watermark with a length of only 1/10 compared to the case where the sampling of the 10-second length largely fails to extract the watermark. In this study, since the length of the watermark embedded into music is 72 bits, it provides sufficient capacity to embed necessary information for music. It is enough bits to identify the music distributed all over the world. 272 can identify $4*10^{21}$, so it can be used as an identifier and it can be used for copyright protection of high quality music service. The proposed algorithm can be used not only for high quality audio but also for development of watermarking algorithm in multimedia such as UHD (Ultra High Definition) TV and high-resolution image. In addition, with the development of digital devices, users are demanding high quality music in the music industry, and artificial intelligence assistant is coming along with high quality music and streaming service. The results of this study can be used to protect the rights of copyright holders in these industries.

Hybrid of the fuzzy logic controller with the harmony search algorithm to PWR in-core fuel management optimization

  • Mahmoudi, Sayyed Mostafa;Rad, Milad Mansouri;Ochbelagh, Dariush Rezaei
    • Nuclear Engineering and Technology
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    • v.53 no.11
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    • pp.3665-3674
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    • 2021
  • One of the important parts of the in-core fuel management is loading pattern optimization (LPO). The loading pattern optimization as a reasonable design of the in-core fuel management can improve both economic and safe aspects of the nuclear reactor. This work proposes the hybrid of fuzzy logic controller with harmony search algorithm (HS) for loading pattern optimization in a pressurized water reactor. The music improvisation process to find a pleasing harmony is inspiring the harmony search algorithm. In this work, the adjustment of the harmony search algorithm parameters such as the bandwidth and the pitch adjustment rate are increasing performance of the proposed algorithm which is done through a fuzzy logic controller. Hence, membership functions and fuzzy rules are designed to improve the performance of the HS algorithm and achieve optimal results. The objective of the method is finding an optimum core arrangement according to safety and economic aspects such as reduction of power peaking factor (PPF) and increase of effective multiplication factor (Keff). The proposed approach effectiveness has been tried in two cases, Michalewicz's bivariate function problem and NEACRP LWR core. The results show that by using fuzzy harmony search algorithm the value of the fitness function is improved by 15.35%. Finally, with regard to the new solutions proposed in this research it could be used as a trustworthy method for other optimization issues of engineering field.

HS Implementation Based on Music Scale (음계를 기반으로 한 HS 구현)

  • Lee, Tae-Bong
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.5
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    • pp.299-307
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    • 2022
  • Harmony Search (HS) is a relatively recently developed meta-heuristic optimization algorithm, and various studies have been conducted on it. HS is based on the musician's improvisational performance, and the objective variables play the role of the instrument. However, each instrument is given only a sound range, and there is no concept of a scale that can be said to be the basis of music. In this study, the performance of the algorithm is improved by introducing a scale to the existing HS and quantizing the bandwidth. The introduced scale was applied to HM initialization instead of the existing method that was randomly initialized in the sound band. The quantization step can be set arbitrarily, and through this, a relatively large bandwidth is used at the beginning of the algorithm to improve the exploration of the algorithm, and a small bandwidth is used to improve the exploitation in the second half. Through the introduction of scale and bandwidth quantization, it was possible to reduce the algorithm performance deviation due to the initial value and improve the algorithm convergence speed and success rate compared to the existing HS. The results of this study were confirmed by comparing examples of optimization values for various functions with the conventional method. Specific comparative values were described in the simulation.

XML Schema Model of Great Staff Music Score using the Integration Method (통합 방식을 이용한 대보표 악보의 XML 스키마 모델)

  • 김정희;곽호영
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.2
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    • pp.302-313
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    • 2003
  • Currently, DTD(Document Type Definition) Definition of Music score has been widely studied according to applications, and the methods of automatic transformation from defined DTD to XML Schema is in progress. In addition, studies of structure of DTD definition are focused on the expression of music information by individual format. In this paper, expression method of the music information by continuous string values is suggested using the fact that measure is basically a component of score, and XML Schema is also modelled. In addition, mechanism extracting the music information from XML instance which was expressed using the proposed method is presented. As a result, XML Schema taking the continuous string values could be defined, instance obtained by the proposed method results in increasing efficiency by simplicity of XPATH and reduction of search step compared to previous method. In addition, it is possible for human to make direct expression, and it is known that the instance size decreases.